SessionEngineering trackconfirmed
Compression at the Edge
- Day
- Day 4 — Session Day 3 · Thu, Jul 2
- Time
- 2:25pm-2:45pm
- Room
- Track 4 · Room 2009
- Track
- Local AI
Track theme
Local AI
Running AI locally / on-device. Session titles are still TBA; theme is taken from the track label.
Accessible with the Engineering pass and above.
About this session
Compression at the Edge examines how smaller weights, faster inference, and constrained-memory deployments are making capable local AI more practical. The panel explores where compressed models already beat cloud on latency, privacy, cost, or control, what breakthroughs would unlock broader adoption, and how open model tooling is shaping the edge AI stack.
Moderator: Chris Alexiuk (NVIDIA). Panelists: Daniel Han (Unsloth), Asma Beevi (NVIDIA), Merve Noyan (Hugging Face), Michael Chiang (Ollama).
